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Microalgae are capable of synthesizing a diverse range of biologically active compounds, including omega-3 fatty acids, carotenoids, proteins, and polysaccharides, which demonstrate significant value in the fields of functional foods, innovative pharmaceuticals and high-value cosmetics. With advancements in biotechnology and the increasing demand for natural products, studies on the functional components of algae have made significant strides. However, the commercial utilization of algal bioactives still faces challenges, such as low cultivation efficiency, limited component identification, and insufficient health evaluation. Artificial intelligence (AI) has recently emerged as a transformative tool to overcome these technological barriers in the production, characterization, and application of algal bioactive ingredients. This review examines the multidimensional mechanisms by which AI enables and optimizes these processes: (1) AI-powered predictive models, integrated with machine learning algorithms (MLAs), Industry 4.0, and other advanced digital systems, support real-time monitoring and control of intelligent bioreactors, allowing for accurate forecasting of cultivation yields and market demand. (2) AI facilitates in-depth analysis of gene regulatory networks and key metabolic pathways, enabling precise control over the biosynthesis of targeted compounds. (3) AI-based spectral imaging and image recognition techniques enable rapid and reliable identification, classification, and quality assessment of active components. (4) AI accelerates the transition from mass production to the development of personalized medical and functional nutritional products. Collectively, AI demonstrates immense potential in enhancing the yield, refining the characterization, and expanding the application scope of algal bioactives, unlocking new opportunities across multiple high-value industries.
Guo et al. (Sat,) studied this question.